Systems and methods for interference mitigation in heterogeneous networks

ABSTRACT

Disclosed systems and methods mitigate interference in heterogeneous networks. Embodiments include adaptive or selective inter-cell interference coordination, adaptive multi-user zero forcing, adaptive power, and/or combinations of the foregoing. Techniques may be used to favor one group of users (e.g., femto users or macro users) over another. Certain embodiments focus quality of service (QoS) improvements on a first group of users, while using constraint processes to provide a threshold QoS for a second group of users.

RELATED APPLICATION

This application claims the benefit under 35 U.S.C. §119(e) of U.S.Provisional Application No. 61/648,426, filed May 17, 2012, which ishereby incorporated by reference herein in its entirety.

TECHNICAL FIELD

This disclosure relates to communication networks. Specifically, thisdisclosure relates to systems and methods for mitigating interference inheterogeneous networks.

BACKGROUND

A need for higher data rates in wireless communication systems hasarisen from a rapid advancement of wireless handheld devicetechnologies. To cover the need for increased capacity, heterogeneousnetworks were introduced. Heterogeneous networks include a hierarchicaldeployment of low power, small footprint stations to increase systemcapacity and coverage within a larger coverage area. For example, femtocells, pico cells, relays, and/or distributed antennas may be usedwithin a macro cell coverage area. However, the femto cells, pico cells,relays, and/or distributed antennas interfere with the time andfrequency resources of the macro cell to cause degradation in cell edgethroughput.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are block diagrams illustrating a heterogeneous network.

FIG. 2 is a flow chart of an example method according to a first type ofadaptive power embodiment.

FIG. 3 is a flow chart of an example method according to a second typeof adaptive power embodiment.

FIG. 4 is a simplified block diagram of a heterogeneous networkconfigured to implement one or more of the embodiments described herein.

FIG. 5 schematically illustrates a femto dual strip deployment modelused to model femto station deployment according to one embodiment.

FIG. 6 is a graph illustrating SINR distributions for macro-onlyscenarios according to an example model.

FIG. 7 is a graph illustrating SINR distributions for femtoheterogeneous network scenarios according to the example model.

FIG. 8 is a block diagram illustrating an ICIC frame structure includingresource blocks for a macro station and femto stations according to oneembodiment.

FIG. 9 is a block diagram illustrating the heterogeneous network shownin FIG. 1B configured to use adaptive inter-cell interferencecoordination with a location-based approach according to one embodiment.

FIG. 10A is a graph of SINR distributions according to certainembodiments.

FIG. 10B is a graph of spectral efficiency distributions according tocertain embodiments.

FIG. 11 is a block diagram illustrating a heterogeneous networkconfigured to perform adaptive multi-user zero-forcing according to oneembodiment.

FIG. 12 is a flow chart of an example method for femto focused adaptivepower adaptation according to one embodiment.

FIG. 13 is a flow chart of an example method using femto focusedadaptive power adaptation with macro constraint according to oneembodiment.

FIG. 14 is a graph illustrating femto station power after applyingadaptive power and adaptive power with macro constraint according tocertain embodiments.

DETAILED DESCRIPTION

A detailed description of systems and methods consistent withembodiments of the present disclosure is provided below. While severalembodiments are described, it should be understood that disclosure isnot limited to any one embodiment, but instead encompasses numerousalternatives, modifications, and equivalents. In addition, whilenumerous specific details are set forth in the following description inorder to provide a thorough understanding of the embodiments disclosedherein, some embodiments can be practiced without some or all of thesedetails. Moreover, for the purpose of clarity, certain technicalmaterial that is known in the related art has not been described indetail in order to avoid unnecessarily obscuring the disclosure.

I. INTRODUCTION

Heterogeneous networks provide a cost-effective way to increase systemcapacity and coverage in third generation partnership project (3GPP)long term evolution (LTE) networks, worldwide interoperability formicrowave access (WiMAX) IEEE 802.16p networks, and networks accordingto other standards. By way of example, embodiments discussed herein aredirected to reducing interference in a femto cell deployed withinbuilding (e.g., house, apartment, office building, or other structure)in a macro cell coverage area. Persons skilled in the art will recognizefrom the disclosure herein, however, that other types of heterogeneousnetworks may also be used including, for example, networks that includepico cells, micro cells, relays, distributed antennas, or othercomponents that may interfere with one another or with a base station ormacro cell. Further, skilled persons will recognize that the disclosureis not limited to indoor deployment of femto stations or other stations,and that an intended coverage area of a femto station may includeoutdoor locations, indoor locations, or a combination of outdoor andindoor locations.

In an example embodiment described herein, one or more femto stationsprovide coverage and capacity enhancement for indoor subscribers who area part of a closed subscription group (CSG). Thus, CSG subscribers' userequipment (UE) may be associated with and communicate through one ormore of the femto stations. On the contrary, indoor UEs or other UEsthat are within a coverage area of the femto stations, but which are notpart of the CSG, are not allowed to associate with or communicatethrough the femto stations. Rather, the non-CSG UEs are generallyassociated with and communicate through the closest macro station.

For purposes of discussion herein, a UE that is associated with andcommunicates through a femto station is referred to as a “femto UE,”while a non-CSG UE that communicates through a macro station is referredto as a “macro UE.” Also, a macro UE that is currently in a buildingcovered by a femto station, or that is otherwise within the coveragearea of the femto station (whether indoors or outdoors), is referred toherein as a “macro indoor UE.” Further, a macro UE that is currentlyoutside of a building covered by a femto station, or that is otherwiseoutside the coverage area of the femto station (whether indoors oroutdoors), is referred to herein as a “macro outdoor UE.” The UEs (e.g.,femto UEs, macro indoor UEs, and macro outdoor UEs) may include, but arenot limited to, mobile phones such as smart phones, personal digitalassistants (PDAs), tablet computers, laptop computers, desktopcomputers, or the like. According to one embodiment, a UE may include amobile information processing device running a mobile operating systemsuch as MeeGo®, Android®, iOS®, Windows Phone®, or the like.

Despite the significant indoor gains expected from deploying femtostations, there are numerous challenging technical problems, such as theinterference between femto stations and macro stations. Interferencemitigation techniques related to femto stations in heterogeneousnetworks include inter-cell interference coordination (ICIC) based onresource management and allocation, multi-user zero forcing (MUZF)beamforming based on using antenna diversity to direct transmission, andpower control techniques based on adjusting the transmitted power oneach resource to guarantee a certain quality of service (QoS) for theUEs.

Generally, ICIC depends on shutting off the femto resources over somepart of their transmission so that a corresponding area of the frame isinterference free. For example, FIGS. 1A and 1B are block diagramsillustrating a heterogeneous network 100 including a macro evolved nodeB (eNB) 110 and a plurality of lower power communication nodes, which inthis example are femto stations 112, 114, 116. The macro eNB and thefemto stations 112, 114, 116 each include a transceiver including one ormore antennas and processors for transmitting radio frequency (RF)signals. In this example, there are two macro users 118, 120 (i.e.,users with macro UEs) within the transmission coverage area 122 of themacro eNB 110. By way of example, FIGS. 1A and 1B also show one femtouser 123, 124, 126 within each transmission coverage area 128, 130, 132of the respective femto stations 112, 114, 116.

As shown in FIG. 1A, the macro eNB 110 assigns a set of macro resourceblocks 134 to the macro user 118 and a set of macro resource blocks 136to the macro user 120. Similarly, the femto station 112 assigns a set offemto resource blocks 138 to the femto user 123, the femto station 114assigns a set of femto resource blocks 140 to the femto user 124, andthe femto station 116 assigns a set of femto resource blocks 142 to thefemto user 126. The resource blocks 134, 136, 138, 140, 142 may includetime resources, frequency resources, processing resources, and/or otherresources used by the macro eNB 110 and the femto stations 112, 114, 116to communicate with the UEs of the respective users 118, 120, 123, 124,126.

In FIG. 1B, the macro user 120 enters a building 144 and the UE of themacro user 120 changes from a macro outdoor UE to a macro indoor UE.Interference between the macro eNB 110 and the femto station 112,however, may cause the macro user 120 to be dissatisfied with the speedand/or quality of communication within the building 144. To solve orreduce the problem, the ICIC technique shuts off a certain percentage ofthe femto resource blocks 138, 140, 142. In FIG. 1B, the darkened blocksrepresent turned off resources in the femto resource blocks 138, 140,142. The ICIC technique increases cell edge performance in heterogeneousnetworks, but the performance is still low compared to homogeneousnetwork cell edge performance. Further, by shutting off a percentage ofthe femto resources, the ICIC technique reduces the capacity of thefemto stations 112, 114, 116.

Generally, the MUZF beamforming technique uses multiple antennas todirect the femto station transmission on an orthogonal channel to macroUE transmission. The femto station determines the macro transmissiondirection from an uplink transmission reaching the femto station. Eachfemto station estimates the channel(s) towards its neighboring macroindoor UE(s) from the uplink transmission of the macro UE. Then, eachfemto station obtains the orthogonal direction to the space spanned bythe macro UE and multiplies its transmitted signal by the null spacematrix so that its effect on macro indoor UEs is minimized. Macro usersare satisfied because the interference is much less, but femto UEssuffer a decrease in power. Further, if a femto user happens to stand ina position where the macro UE is located, there may be a problem incoverage for the femto UE.

Power control techniques include an adaptive power (AP) scheme thattargets the benefit of both macro UEs and femto UEs, while keeping thepower at efficient usage levels. The AP scheme adjusts the power offemto stations independently to satisfy a QoS parameter for a certaingroup of users. The AP scheme may be referred to as non-unanimousbecause, under normal conditions, each femto station acts independentlyfrom other stations to satisfy the needs of its surrounding users.

A first type of AP focuses on satisfying a femto QoS by decreasing thefemto power to thereby increase the macro indoor UE'ssignal-to-interference-plus-noise-ratio (SINR) and to satisfy a certainfemto SINR performance. An aim of the first type of AP is to avoiddecreasing capacity at the same time as increasing cell edgeperformance. FIG. 2 is a flow chart of an example method 200 accordingto the first type of AP. The method 200 begins by setting 210 the femtostations to a low power. The femto stations associate with respectivefemto UEs, and the SINR of each femto UE is measured. For each femto UE,the method 200 then queries 211 whether the measured femto SINR is lessthan a targeted femto UE QoS. If not, the method ends 212. If, on theother hand, the measured femto SINR of the femto UE is lower than thetargeted SINR, the method 200 reports 214 the particular UE to the femtostation attached thereto and queries 216 whether the femto station poweris less than a maximum power.

If the femto station power is greater than the maximum power, theprocess ends 218. If, however, the femto station power is less than themaximum power, the method 200 increments 220 the attached femtostation's power and reattaches all users based on the new power plan.Then, to determine whether the femto SINR is fulfilled, the method 200again queries 211 whether the femto SINR is less than the femto UE QoS,reports 214, and queries 216 whether the femto station power is lessthan the maximum power. When the SINR of all femto UEs is satisfied, thepower is not increased. Also, if femto stations reach maximum power, nomore increase can be done. Thus, instead of all femto stationstransmitting at full power, the power of most femto cells is decreaseddramatically.

A second type of AP focuses on macro UEs by attempting to satisfy acertain macro UE QoS. In the second type of AP, the femto station startsat a high power. If the femto station causes interference such that amacro UE has lower QoS than it should, the femto station decrements itspower to provide for lower interference and higher QoS at the macro UE.FIG. 3 is a flow chart of an example method 300 according to the secondtype of AP. The method 300 begins by setting 310 the femto stations to anormal operating power and measuring the SINR of each macro UE. For eachmacro UE, the method 300 then queries 312 whether the measured macroSINR is less than a targeted macro UE QoS. If not, the method ends 314.If, on the other hand, the measured macro SINR is lower than thetargeted SINR, the method 300 reports 316 to the interfering femtostations and queries 318 whether the femto station power is greater thana minimum power. If the femto station power is less than the minimumpower, the method 300 ends 320. If, however, the femto station power isgreater than the minimum power, the method 300 decrements 322 the femtostation's power and reattaches all users based on the new power plan.Then, to determine whether the macro SINR is fulfilled, the method 300again queries 312 whether the macro SINR is less than the target macroUE QoS, reports 316, and queries 318 whether the femto station power isgreater than the minimum power. The method 300 improves the performanceof the macro UEs through satisfying a certain QoS and providessatisfaction for femto users as they all start at the highest power andonly the ones affecting macro UEs are degraded.

Generally, however, sharing resources or reducing the femto station'spower for all deployed femto stations results in lower femto throughput,which in turn limits the expected gains from the deployed femtostations. Thus, according to certain embodiments disclosed herein,adaptive techniques are used to selectively apply ICIC, MUZF, and/orpower control techniques only to the femto stations that currently causean unacceptable level of interference.

As discussed in detail below, deploying femto cells increases the SINRof femto UEs and may cause limited degradation to the performance of theoutdoor macro UEs. However, the applicants have recognized that themacro indoor UEs are “victim” UEs of prior attempts at interferencemitigation. In other words, prior attempts at interference mitigationhave dramatically reduced the SINR performance of the macro indoor UEs.Thus, embodiments disclosed herein are directed to improving theperformance of macro indoor UEs while preserving high throughput of thefemto UEs. In certain embodiments, an adaptive ICIC (A-ICIC) techniqueis used wherein a femto station detects neighboring UEs and, if itdetects a macro UE in its neighborhood (i.e., intended coverage area),periodically turns off a portion of its resources. Otherwise, the femtostation utilizes all available resource blocks (RBs). In otherembodiments, an adaptive multi-user zero-forcing (A-MUZF) technique isused wherein each femto cell is configured to selectively apply anulling algorithm to null the femto interference to the nearby macroUEs. In other embodiments, adaptive power ICIC (AP-ICIC) or adaptivepower MUZF (AP-MUZF) apply power control on top of A-ICIC or A-MUZF,respectively. As discussed below, each of these disclosed embodimentscan significantly increase the throughput of the macro indoor UEs, whilemaintaining the high throughput achieved by deploying femto stations.

In one A-ICIC embodiment, a femto station detects the presence of amacro UE in the neighborhood (e.g., in the femto station's intendedcoverage area) through received power information or locationinformation. The femto station may detect, for example, the highestreceived power from the macro UE to the femto station. The femto stationmay also detect the presence in the location by detecting the presenceof the macro UE in the same building (e.g., apartment) as a femto UE. Afemto station that recognizes the macro UE in the neighborhood shuts offtransmission on a percentage of its resource blocks. The percentage ofshut off resources may vary according to the needed capacity versusneeded improvement of the cell edge users (e.g., as percentage of shutoff increases, network capacity decreases and cell edge throughputincreases). The resource blocks may include time resource blocks and/orfrequency resource blocks.

In one embodiment, selective inter-cell interference coordination(S-ICIC) includes a femto station configured to shut off a percentage ofits resource blocks. The percentage of shut off resources variesaccording to the needed capacity versus needed improvement of the celledge users (e.g., as percentage of shut off increases, network capacitydecreases and cell edge throughput increases). The resource blocks mayinclude time resource blocks and/or frequency resource blocks. Incertain embodiments, only cell edge users are scheduled (attached) tofemto interference free resources.

In certain embodiments, AP is used with macro constraint (MC), which maybe referred to herein as AP-MC. In such embodiments, femto stationsoperate at their minimum operation power and each femto station detectsa QoS parameter of a femto user group. If the QoS parameter is notsatisfied for a femto UE, the femto station detects the presence ofmacro UEs through a power-based approach. For example, the femto stationmay detect the presence of a macro UE by receiving power from the macroUE. If the QoS parameter of the macro UE is satisfied, the femto stationincrements the femto station's power to satisfy the QoS of the femtoUEs, or else no action is taken. If the femto station reaches its normaloperating power, no further action is taken.

In certain embodiments, AP is used with femto constraint (FC), which maybe referred to herein as AP-FC. In such embodiments, femto stationsoperate at their normal operation power. Each femto station detects thepresence of macro UEs through a power-based approach. For example, afemto station detects the presence of a macro UE if it receives powerfrom the macro UE. The femto station then detects a macro UE QoSparameter. If the Macro UE QoS parameter is not satisfied, the QoS ofthe femto UEs attached to the femto station is detected. If the QoSparameter of Femto UEs is satisfied, the femto station decrements itspower to satisfy the QoS of the macro UEs, or else no action is taken.If the femto station reaches its minimum power, no further action istaken.

In certain embodiments, adaptive power inter-cell interferencecoordination (AP-ICIC) is used wherein a femto station performs both atype of ICIC and a type of AP. In one embodiment, the type of ICICincludes the ICIC method described above wherein the femto station shutsoff a percentage of its resource blocks. The percentage of shut offresources may vary according to the needed capacity versus neededimprovement of the cell edge users (e.g., as the percentage of shut offincreases, network capacity decreases and cell edge throughputincreases). The resource blocks may be time resource blocks and/orfrequency resource blocks. Any macro user may be assigned to a femtofree resource. In another embodiment, the type of ICIC may be A-ICIC, asdescribed above. In another embodiment, the type of ICIC may be S-ICIC,as described above. In one embodiment, the type of AP includes a femtofocused AP wherein the femto station collects the value of a QoSparameter from the femto UEs. The QoS parameter threshold value is basedon the performance of the UEs without interference mitigation. If themacro UE QoS is not satisfied, the femto station increases its poweruntil the QoS parameter is satisfied or the femto station reaches itsmaximum or minimum power. In another embodiment, the type of AP includesa macro focused AP wherein the femto station determines a QoS parameterfor macro UEs. The QoS parameter threshold is based on the performanceof the UEs without interference mitigation. If the QoS is not satisfied,the femto station decreases its power until the QoS parameter issatisfied or the femto station reaches its maximum or minimum power.

In one embodiment, adaptive power adaptive multi-user zero forcing(AP-A-MUZF) is used wherein a femto station detects the macro UEs in theneighborhood by received power or location. The femto station detectsthe macro UE uplink. The femto station estimates channel(s) towards itsneighboring macro indoor UE(s) and obtains the orthogonal to the spacespanned by the macro UE(s). The femto station multiplies its transmittedsignal by the null space matrix to minimize its effect on the macroindoor user. The femto station detects a QoS parameter for a group ofusers (e.g., femto UEs or macro UEs). If the QoS is not satisfied, thefemto station adjusts its power until the QoS parameter is satisfied orthe femto station reaches its maximum or minimum power.

In one embodiment, an adaptive power with constraint-ICIC (AP-C-A-ICIC)is used wherein a femto station detects the presence of a macro UE inthe neighborhood through power received or location. The femto stationthat recognizes the macro UE in the neighborhood shuts off transmissionon a percentage of its resource blocks (e.g., time and/or frequencyresource blocks). Each femto station detects a QoS parameter of acertain user group. If the QoS parameter is not satisfied for a firstgroup, the femto station detects the presence of UEs from a secondgroup. If the QoS parameter of the second group is satisfied, the femtostation adjusts its power to satisfy the QoS of the first group orreaches its maximum or minimum power, or else no further action istaken.

These and other embodiments are described below. Skilled persons willrecognize from the disclosure herein that two or more of the describedembodiments may be combined.

II. EXAMPLE SYSTEM MODEL

For purposes of discussion, an example model is provided of a simpleheterogeneous cellular network. Skilled persons will recognize from thedisclosure herein that other types of heterogeneous networks (includingthose with femto cells, pico cells, relays, distributed antennas, andcombinations of the foregoing) may be used.

FIG. 4 is a simplified block diagram of a heterogeneous network 400configured to implement one or more of the embodiments described herein.The network 400 includes a macro station 410, a femto station 412, amacro outdoor UE 414, a macro indoor UE 416, and a femto UE 418. Themacro UEs 414, 416 and the femto UE 418 may be mobile devices that userstransport into and out of a macro coverage area 420 of the macro station410 and/or a femto coverage area 422 of the femto station 412. In theexample shown in FIG. 4, the femto station 412 is located in or near ahouse 424. However, any type of building or other location (includingoutdoor locations) may be used. In addition, or in other embodiments,one or more of the macro UEs 414, 416 and femto UE 418 may be a fixed ornon-mobile device. In the example shown in FIG. 4, the macro UEs 414,416, femto station 412, and femto UE 418 are located within the macrocoverage area 420. Further, the macro indoor UE 416 and the femto UE 418are located within the femto coverage area 422. As discussed above, thefemto UE 418 may be part of a CSG associated with the femto station 412.In this example, however, the macro indoor UE 416 is not subscribed tothe CSG, and hence it (like the macro outdoor UE 414) is associated withthe macro station 410. The dashed line between the femto station 412 andthe macro indoor UE 416 represents an interference signal.

In the example model, the network 400 shown in FIG. 4 is expanded toinclude L macro stations (such as the macro station 410) and M femtostations (such as the femto station 412). The received signal at a macrouser served by the K^(th) macro station (referred to as macro-user K)can be given by

$\begin{matrix}{{y_{k} = {{\sqrt{\alpha_{k}}H_{k}w_{k}x_{k}} + {\sum\limits_{\underset{i \neq k}{i = 1}}^{L}{\sqrt{\alpha_{i}}H_{i,k}W_{i}x_{i}}} + {\sum\limits_{j = 1}^{M}{\sqrt{\beta_{j}}H_{j,k}Q_{j}s_{j}}} + n_{k}}},} & (1)\end{matrix}$where H_(k); H_(i,k); H_(j,k) denote channels from the serving macrostation, the i^(th) macro station, and the j^(th) femto station to ak^(th) macro user, respectively, of size N_(r)×N_(t). Also, α and βrepresent the path loss attenuation factor.

Further, x_(k) denotes the transmitted signal to the k^(th) macro-userof size N_(t)×1 and s_(j) denotes the transmitted signal to the j^(th)femto user of size d×1, where d depends on the transmission techniquediscussed below. n_(k) denotes zero mean additive white Gaussian noise(AWGN) of the k^(th) macro user and Q is a femto precoding matrix ofsize N_(t)×d. W is a standard 3GPP macro precoding matrix of sizeN_(t)×N_(t).Let {tilde over (Q)}=HQ and {tilde over (W)}=HW.  (2)

It is assumed that there is one spatial stream only being transmittedfrom any of the macro or femto stations. It can be shown from equation(1) that the SINR of the k^(th) macro-user can be represented as

$\begin{matrix}{{\gamma_{k} = \frac{\alpha_{k}{{\sum\limits_{n = 1}^{N_{t}}{{\overset{\sim}{W}}_{k}\left( {:{,n}} \right)}}}}{{\sum\limits_{\underset{i \neq k}{i = 1}}^{L}{\alpha_{i}{{\sum\limits_{n = 1}^{N_{t}}{{\overset{\sim}{W}}_{i}\left( {:{,n}} \right)}}}}} + {\sum\limits_{j = 1}^{M}{\beta_{j}{{\sum\limits_{n = 1}^{d}{{\overset{\sim}{Q}}_{j}\left( {:{,n}} \right)}}}}} + \sigma_{k}^{2}}},} & (3)\end{matrix}$where σ_(k) ² denotes the variance of n_(k). Similarly, the receivedsignal of the j^(th) femto user can be represented as

$\begin{matrix}{{y_{j} = {{\sqrt{\beta_{j}}H_{j}Q_{j}s_{j}} + {\sum\limits_{k = 1}^{L}{\sqrt{\alpha_{k}}H_{k,j}W_{k}x_{k}}} + {\sum\limits_{k = 1}^{M}{\sqrt{\beta_{i}}H_{i,j}Q_{i}s_{i}}} + n_{j}}},} & (4)\end{matrix}$and its SINR is given by

$\begin{matrix}{\gamma_{j} = {\frac{\beta_{j}{{\sum\limits_{n = 1}^{d}{{\overset{\sim}{Q}}_{j}\left( {:{,n}} \right)}}}}{{\sum\limits_{k = 1}^{L}{\alpha_{k}{{\sum\limits_{n = 1}^{N_{t}}{{\overset{\sim}{W}}_{k}\left( {:{,n}} \right)}}}}} + {\sum\limits_{\underset{i \neq j}{i = 1}}^{M}{\beta_{i}{{\sum\limits_{i = 1}^{d}{{\overset{\sim}{Q}}_{i}\left( {:{,n}} \right)}}}}} + \sigma_{j}^{2}}.}} & (5)\end{matrix}$

In order to model the complete heterogeneous network, a system levelsimulator (SLS) is used that follows the IEEE 802.16 evaluationmethodology document for the downlink. In addition, the dual stripdeployment model is used to model the femto cell deployment.

A. System Level Simulations

In the simulations described herein, which are provided by way ofexample only and are not necessary to practice the embodiments disclosedherein, the SLS simulates the deployment of 19 hexagonal cells. Eachcell includes a macro base station at its center and threenon-overlapping sectors. The network configuration parameters include:number of cells is 19; sectors per cell is 3; inter-cell distance is1500; UEs per sector is 14; frames per trial is 100; number of trials is100; carrier frequency is 2.5 GHz; frequency reuse factor is 1; and cellload is 100%.

Each UE experiences slow fading phenomenon, such as shadowing and pathloss, as well as fast fading channel behavior. The SLS models theevolution of the desired signal and interference received by the UE intime, and employs a PHY abstraction model to predict the link layerperformance. Then, a suitable modulation and coding scheme (MCS) isassigned based on the SINR value. Table 1 depicts system modelparameters used in the simulation:

TABLE 1 System Model Parameters PARAMETER VALUE Channel Model ExtendedITU PedB (3 km/h) Antenna configuration 4 × 2 Base station (BS) tx power47 dBm Femto station (FS) tx power 20 dBm BS antenna pattern 70 (−3 dB)with 20 dB front-to-back ratio BS antenna gain 17 dB FS antenna gain 5dB BS antenna spacing 0.5 wavelength SS antenna pattern Omni-directionalSS antenna gain 0 dB SS antenna spacing 0.5 wavelength Cable loss 2 dBDetection MMSE Scheduling Proportional fairness Noise figure 7 dB MCSQPSK (R = 1/12, ⅛, ¼, ½, ¾), 16-QAM (R = ½, ¾), 64-QAM (R = ½, ⅔, ¾, ⅚)

Each user is allocated one or more resource blocks (RBs) based onproportional fairness (PF) scheduling criterion. Each frame has a totalof 12 RBs, each including 4 frequency sub-channels and 24 orthogonalfrequency division multiplexing (OFDM) symbols. Table 2 shows details ofthe OFDMA air interface values.

TABLE 2 OFDMA Parameters PARAMETER VALUE System bandwidth 10 MHz FFTsize 1024 Subcarrier spacing 10.9375 KHz Data sub carriers  768 CPlength ⅛ OFDMA symbol duration 102.86 μsec Permutation LRU Frameduration 5 msec Sub-channels/Frame  48

The SLS provides a list of performance criteria that includes thecumulative distribution function (CDF) of the users' SINR distributions,users' average throughput, and aggregate sector throughput. Theaggregate sector throughput is defined as the number of information bitsper second that the sector can successfully deliver. The user and sectorspectral efficiency (SE) (in bps/Hz) are calculated by dividing therespective throughput by the channel bandwidth, as

$\begin{matrix}{{{SE} = \frac{R}{W}},} & (6)\end{matrix}$where R is the aggregate throughputs, and W is the total bandwidth. Inaddition, the cell edge user SE is calculated, which corresponds to the5% level of the CDF of the users' spectral efficiency.

B. Femto Dual Strip Deployment Model

FIG. 5 schematically illustrates a femto dual strip deployment modelused to model femto station deployment according to one embodiment.Blocks 500 like the one shown in FIG. 5 are distributed randomly over anetwork. Each block 500 has two apartment strips 510, 512 with 2×Napartments in each strip. Each apartment has an area of 10×10 m².Between the two strips of apartments there is a 10 m wide street 514.Also, streets surround the two strips 510, 512, as shown in FIG. 5.Macro indoor users are distributed randomly across the femto blockfloors, and the rest of the macro users are outdoors. Femto stations areinstalled in the apartments according to the deployment ratio from theapartments. Some of the femto stations are activated and some aredeactivated according to the activation ratio. In the example model,each femto station includes one femto UE located in the same apartment.

TABLE 3 Simulation Parameters of the Femto Block PARAMETER VALUE N(number of cells per row) 10 M (number of clusters per sector) 1 L(number of floors per cluster) 1 R (deployment ratio) 20% P (activationratio) 80% Percentage of macro UEs being indoors 60%

C. Model Analysis

Analysis of the model described above reveals problems with femtoheterogeneous networks. First, as a reference case, consider themacro-only scenario which has macro stations only with no deployment offemto stations. To clearly understand the femto impact, the outdoor andindoor macro UEs are distinguished and it is noted that only the macroindoor UEs undergo the indoor penetration loss. FIG. 6 is a graphillustrating SINR distribution CDFs for the macro-only scenarioaccording to the example model. As shown, the macro indoor UEs and themacro outdoor UEs have almost the same SINR distributions. In otherwords, the indoor penetration loss has little or no impact on the SINRvalue. This is true because both the desired signal and interferencesignals are reduced by the same value. Thus, the SINR ratio issubstantially the same.

Second, consider the impact of deploying femto stations on the SINR ofall the UEs. FIG. 7 is a graph illustrating SINR distribution CDFs forthe femto heterogeneous network scenario according to the example model.As shown in FIG. 7, the femto UEs have large SINR, which is the desiredimpact of deploying femto stations. This is because femto UEs experiencehigh desired signal power and low interference power. Comparing FIG. 7to FIG. 6, it is shown that the macro outdoor UEs have no degradationdue to the deployment of the femto stations. This is because the outdoorUEs receive low interference levels from the femto stations. However,the macro indoor UEs have dramatic degradation as the macro indoor UEsreceive a large amount of interference from the femto stations. Thus,the applicants conclude that the macro indoor UEs are the victim UEs,which suffer the most from deploying the femto stations.

Embodiments disclosed herein of interference aware femto cells reduce oreliminate this impact on the macro indoor UEs, while preserving the highthroughput of the femto UEs.

III. RESOURCE ALLOCATION TECHNIQUES FOR INTER-CELL INTERFERENCECOORDINATION (ICIC)

In the typical ICIC algorithm, as discussed above, all of the femtostations do not transmit any data for a number of RBs. For example, FIG.8 is a block diagram illustrating an ICIC frame structure including RBs810 for a macro station and RBs 812 for all femto stations. In FIG. 8,all the femto stations are silent (represented by darkened blocks) for50% of the RBs 812. On the contrary, the macro stations transmit theirdata across all the RBs 810. However, in a case where a particular femtostation is not causing interference to any nearby macro indoor UE, thereis no need to make that femto station silent over some of its RBs 812.Thus, a smart femto station is disclosed that detects the neighboringmacro UEs and acts according to their status.

A. Selective ICIC (S-ICIC)

In S-ICIC, the femto stations schedule or reserve femto free resourcesto the cell edge users only (e.g., including macro indoor UEs). Althoughconventional ICIC gives a great advantage to macro users, its schedulingis not efficient. In contrast to S-ICIC, conventional ICIC assigns someof the femto free resources to the macro outdoor UEs, which are notsuffering reduced performance due to interference from the femtostations. S-ICIC improves the cell edge users above that provided byICIC, and at the same time does not degrade femto users below their ICICoperation. In normal ICIC operation, the capacity of the networkdecreases because some of the femto resources are not used.

B. Adaptive ICIC (A-ICIC)

A problem with S-ICIC and conventional ICIC is that they cause highdegradation in the network capacity when compared with a femto baseline.The capacity degradation is caused by the large percentage of shut offfemto station resources. In A-ICIC, each femto station detects whetherit causes interference over a macro UE. If so, the femto station appliesICIC (e.g., by shutting off 50% of its RBs in a periodic manner, similarto the conventional ICIC). If, on the other hand, the femto station doesnot cause interference over a macro UE, the femto station does notrestrict the use of its RBs (e.g., it may use all of its RBs, ifneeded).

The femto stations may detect the presence of a macro UE in the vicinityusing, for example, a power-based approach or a location-based approach(e.g., an apartment-based approach). In the power-based approach, amacro indoor UE is detected when the power received by the macro indoorUE from the macro station is lower than the power received by the macroindoor UE from the femto station. In certain embodiments, thepower-based approach does not put the limitation that both the macroindoor UE and the femto station need to be in the same femtocelllocation (e.g., apartment).

In the location-based approach, the femto station applies the ICICtechnique if it determines that it is in the same location (e.g.,apartment, house, office, or other building) as a macro UE. For example,FIG. 9 is a block diagram illustrating the heterogeneous network 100shown in FIG. 1B configured to use A-ICIC with a location-based approachaccording to one embodiment. As in FIG. 1B, the macro user 120 entersthe building 144 and the UE of the macro user 120 changes from a macrooutdoor UE to a macro indoor UE. However, unlike the conventional ICICapproach shown in FIG. 1B where each of the femto stations 112, 114, 116shuts off a certain percentage of their respective femto resource blocks138, 140, 142, the A-ICIC method provides that only the femto station112 that detects the macro user 120 within the building 144 shuts off apercentage of its femto resource blocks 138. The other femto stations114, 116 continue to use all of their respective resource blocks 140,142. Thus, femto UEs benefit from A-ICIC as all femto stations (e.g.,femto stations 114, 116) provide normal transmission except the ones(e.g., femto station 112) interfering with a macro UE. Consequently,more femto users are satisfied with the use of the femto UEs. Meanwhile,the macro indoor UEs are provided with a zone free from interference totransmit their data, which leads to a better satisfaction for the macroindoor users.

FIG. 10A is a graph of SINR CDF distributions of macro-only, baselinefemto (no ICIC), and two A-ICIC techniques according to certainembodiments. As shown in FIG. 10A, the location-based (e.g.,apartment-based) A-ICIC technique increases the SINR of the UEs with lowSINR, which are the macro indoor UEs. On the other hand, A-ICIC has noimpact on the UEs with high SINR, which are the macro outdoor UEs.Moreover, FIG. 10A shows that the power-based A-ICIC technique achieveshigher SINR for the macro indoor UEs than the location-based technique,as it avoids interference to the macro indoor UEs from all the adjacentfemto stations as well. Further, note that the SINR of the macro indoorUEs (below 0 dB) is upper-bounded by that achieved by the macro-onlycase (no femto stations are deployed).

FIG. 10B is a graph of the spectral efficiency (SE) CDF distributions ofthe macro-only, baseline femto, and two A-ICIC techniques according tocertain embodiments. The behavior of the SE is a direct result of theSINR, which is shown in FIG. 10A. As shown in FIG. 10B, the portion ofUEs achieving high SE represents the femto UEs. On the other hand, theportion of UEs achieving low SE represents the macro indoor UEs, whichis improved by the two A-ICIC techniques.

Additional advantages of the A-ICIC embodiments are discussed below withrespect to Table 4.

IV. ANTENNA DIRECTION CONTROL FOR ADAPTIVE MULTI-USER ZERO FORCING(A-MUZF)

In A-MUZF beamforming, only femto stations that detect macro UEs in theneighborhood perform MUZF, and femto stations that do not detect nearbymacro UEs transmit normally. For example, FIG. 11 is a block diagramillustrating a heterogeneous network 1100 configured to perform A-MUZFaccording to one embodiment. The network 1100 includes the macro eNB 110with its transmission coverage area 122 and the femto stations 112, 114discussed above with respect to FIG. 1B. The macro indoor user 120 andthe femto users 123, 124 are also shown. In this example, the femtostation 112 detects the presence of the macro indoor user 120 andresponds by applying the MUZF algorithm to reshape the femto coveragearea 128 and avoid interfering with the macro indoor user 120. While themacro indoor user 120 remains in the neighborhood, the femto user 123experiences a slight decrease in power, but the temporary change isgenerally not over burdensome. Because there are no macro users in theneighborhood of the femto station 114, the coverage area 130 of thefemto station 114 remains unchanged and the femto user 124 is notaffected. Thus, the femto UEs benefit from A-MUZF as some of them arenot subjected to any change, while macro UEs benefit from having aninterference free channel to transmit their data through.

In the A-MUZF algorithm, the femto station 112 estimates its channel(s)towards its neighboring macro indoor UE(s) (e.g., corresponding to themacro indoor user 120). The singular value decomposition of H_(j,k) canbe obtained asH _(j,k) =USV ^(H),  (7)where U and V are unitary matrices and S is a diagonal matrix. Then thefemto station 112 obtains the null space, which is orthogonal to thespace spanned by channels of the macro indoor UEs as inQ=null(V(:,1)),  (8)where V(:,1) is the primary eigen vector, Q is null space matrix withdimensions Nt×d where d=Nt−dim(interference subspace) and, since onesingle-rate user is canceled, therefore d=Nt−1. The femto station 112multiplies its transmitted signal, directed to its femto UE (e.g., ofthe femto user 123), by the null space matrix. Note that the macroindoor UEs' channels can be estimated by listening to the uplinkchannel, where the macro indoor UEs send their reference signals in anattempt to associate with the femto station 112. This is possible fortime division duplex (TDD) systems, for example, as the downlink anduplink channels are almost the same. In certain embodiments, thebeamforming is adjusted as the macro indoor UEs move within the coveragearea of the femto station to maintain the null space orthogonal to thespace spanned by channels of the macro indoor UEs. In addition, or inother embodiments, in the A-MUZF technique as in the A-ICIC embodimentsdiscussed above, the location-based (e.g., apartment-based) andpower-based approaches may be used to identify macro UEs in the femtostation neighborhood.

V. ADAPTIVE POWER ICIC AND MUZF

The two schemes described above focus on interference mitigation in onedimension only, either time frequency resource-blocks (as in A-ICIC), orthe spatial domain (as in A-MUZF). In certain embodiments, power controlis also applied on top of these two schemes. Generally, power controlaims to reduce the transmission power of each femto station below itsmaximum value to reduce its interference on the nearby macro UEs, whileguaranteeing required QoS (SINR in this case) for the femto UEs (e.g.,FF-AP). More specifically, all the femto stations have a low initialpower value, which increases (in small steps) until the required SINR ofits associated femto UE is achieved.

In one embodiment, adaptive power inter-cell interference coordination(AP-ICIC) adapts the transmission power of each femto station on thetime-frequency RBs, where femto stations transmit their data. In anotherembodiment, adaptive power multi-user zero forcing (AP-MUZF) appliespower control for the femto station in addition to the nulling precodingdiscussed above.

To characterize the performance gains of the various schemes, theaverage SE delivered by the macro station and femto stations iscalculated. In addition, the total area SE achieved over the totalsector area is calculated, which in this example is the total SEachieved by one macro station and six femto stations. Further, thecell-edge SE achieved by each scheme is calculated. Table 4 summarizesthe results of several different example scenarios.

TABLE 4 Performance Results of Various Scenarios TOTAL MACRO FEMTOSECTOR FSs CELL- SCENARIO SE SE AREA SE AFFECTED EDGE SE Macro-only 2.18— 2.18 — 0.035 Femto base- 1.89 1.74 12.32  0% 0.02 line ICIC 1.96 0.917.43 100%  0.039 Location- 1.9 1.64 11.72 15% 0.021 based A- ICIC Power-1.92 1.41 10.36 37% 0.027 based A- ICIC Location- 1.89 1.71 12.15 15%0.02 based A- MUZF Power-based 1.91 1.6 11.5 37% 0.027 MUZF Power-based2.02 1.56 11.37 24% 0.042 FF-AP-ICIC Power-based 1.99 1.47 10.38 26%0.041 AP-MUZF

Comparing macro-only to femto baseline in Table 4, it is shown thatdeploying femto stations increases the total area (1 macro+6 femtos) SEby 465% (from 2.18 to 12.32). On the other hand, deploying femtostations reduces the cell-edge SE by 42% (from 0.035 to 0.02). Due tosuch loss in the cell-edge SE, the ICIC algorithm was previouslyproposed. Table 4 depicts that the ICIC significantly increases thecell-edge SE to 0.039, achieving gain of 11% in the cell-edge SEcompared to the macro-only case. However, the ICIC reduces the gain inthe total area SE by 241% compared to the macro-only case.

Table 4 shows that the location-based (e.g., apartment-based) A-ICICdoes not increase the cell-edge SE beyond that achieved by the femtobaseline case. This is due to the observation that only 15% of femtostations apply the ICIC algorithm, which is not sufficient to improveall the macro indoor UEs. As for the power-based A-ICIC technique, notethat it increases the cell-edge SE to 0.027, which is still lower thanthat of the macro-only case. Hence, the two A-ICIC techniques increasethe total area SE, however, they achieve lower cell-edge SE compared tothe macro-only case. Looking at the results of the A-MUZF (eitherlocation-based or power-based), note that they give similar performanceto the A-ICIC schemes, with cell-edge SE being lower than that of themacro-only scenario. Thus, it is shown that neither A-ICIC nor A-MUZF,according to certain embodiments, can achieve the needed or desiredcell-edge SE. By considering adaptive power control and focusing only onthe power-based adaptive mode, both femto focused AP-ICIC and AP-MUZFachieve higher cell-edge SE than that of the macro-only case. Further,femto focused AP-ICIC and AP-MUZF achieve very high total sector areaSE. For example, the FF-AP-ICIC achieves total area SE improvement of422% with cell-edge SE improvement of 20%. Similar improvements areachieved by the AP-MUZF scheme.

By way of summary, deploying femto stations increases the SINR of theirassociated femto UEs and has little or no negative impact on the outdoormacro UEs. However, deploying femto stations decreases the SINR of themacro indoor UEs. To improve the performance of the macro indoor UEs,certain embodiments use various interference mitigation algorithmsspanning the time-frequency, spatial, and power dimensions. In certainembodiments, neither the A-ICIC nor the A-MUZF schemes guarantee thebaseline (macro-only) cell-edge SE. However, certain such embodimentsuse AP-ICIC and/or AP-MUZF to improve both the total sector area SE andthe cell-edge SE. Compared to the macro-only case, the AP-ICIC achievestotal area SE improvement of 422% with cell-edge SE improvement of 20%.

VI. ADAPTIVE POWER CONTROL TO SELECTIVELY FAVOR USER GROUPS

Power-control adjusts the femto station power to satisfy either macro orfemto QoS, or power control may simply broadcast a unanimous fixed powerthreshold to all femto stations according to their density. When fixedpower is used, all femto stations unanimously send with the sametransmission power. If, however, a non-unanimous, adaptive power (AP)control is used, every femto station decides on the amount of power thatit transmits based on feedback from the UEs attached to it. APadaptation algorithms focus on either favoring femto users (FF-AP) orfavoring macro users (MF-AP). FF-AP is used to adjust the femtotransmission power to satisfy a target femto SINR to improve the networkcapacity. MF-AP is used to adjust the femto transmission power tosatisfy a target macro SINR.

Certain embodiments disclosed herein use adaptive power inter-cellinterference coordination (AP-ICIC) and/or adaptive power withconstraint (AP-C). AP-ICIC applies ICIC by shutting off the femtotransmission for a percentage of the resource blocks. AP-C is used toavoid jeopardizing the group out of focus. In FF-AP, for example, amacro SINR level constraint may be enforced (FF-AP-MC) such that femtostations do not increase their power more than a certain level that mayaffect a macro UE, hence it does not decrease cell edge. As anotherexample, in MF-AP, a femto SINR level constraint may be enforced(MF-AP-FC) such that femto stations do not decrease their power below acertain level to avoid harming associated femto UE, hence it does notdegrade capacity. AP with its different variations may be applied, alongwith different variations of ICIC, to achieve best or improved valuesfor both cell edge and cell capacity. The following embodiments improvethe UE experience through improving the macro UE (e.g., using ICIC orMUZF) and/or improving the femto UE through AP.

A. AP-ICIC (AP-ICIC, AP-S-ICIC, AP-A-ICIC)

Certain embodiments depend on the femto station applying a type of ICIC(whether conventional, selective, or adaptive) and then applying AP overthe network. Embodiments for selective ICIC (S-ICIC) and conventionalICIC provide a high increase to the macro indoor users' throughput byshutting off femto resources at the same time as applying the low powerof the femto station. In spite of providing for the quality of servicelevel for the femto users, the femto stations do not use a portion oftheir resources such that the network capacity decreases.

For adaptive ICIC (A-ICIC), the femto UEs are not degraded (or are onlyslightly degraded) because not all femto cells are affected. Further,any femto UE performance that was degraded by ICIC may be compensatedthrough AP to reach an acceptable level of QoS, and any macro UEaffected by femto interference may be offered a femto free zone for itstransmission to increase its throughput and improve cell edgeperformance.

B. AP-A-MUZF

In certain embodiments, a femto station applies A-MUZF to guarantee aninterference free zone for the macro UE to transmit its signals. Then,the femto station applies AP to provide femto UEs with a certainthreshold of QoS, which provides needed power to satisfy the femto QoSover the directed transmission. The macro UEs and femto UEs have goodthroughput in such embodiments because each is dealt with independently.AP-A-MUZF provides high cell edge performance and capacity, but may havehigh complexity in certain embodiments, due to the MUZF complexity.

C. Favoring Femto Users through Femto Focused Adaptive Power Adaptation(FF-AP)

While ICIC provides better service for macro users, power adaptation maybe used in certain embodiments to improve performance for femto users.The power control algorithms depend on varying the transmission power ofthe femto station to satisfy a certain QoS of the femto UEs, which isthe SINR. FIG. 12 is a flow chart of an example method 1200 for FF-APaccording to one embodiment. With all femto stations set to a minimumpower, the method 1200 includes the femto UEs reporting 1212 theircurrent SINR to an attached femto station (where the SINR is, e.g., fora QoS parameter). The method 1200 then queries 1214 whether the SINR ofany of the femto UEs is less than a target SINR. If no, then the method1200 ends 1216. If, however, any femto UE SINR is below the target SINR,the method queries 1218 whether the power of the femto stationassociated to the weak user is less than a maximum power (MaxFS) of thefemto station. If no, the method 1200 ends 1220. If, on the other hand,the power of the femto station associated to the user is less than themaximum power, then the femto station associated to the user increases1222 its power. In this example, the femto station increases its powerby an increment of 2 dBm. However, larger or smaller increments may beused. In case of any change in the femto station power, the users arere-associated 1224 to the femto stations in the network based on the newpower plan. Then, the method 1200 repeats until either all femto UEssatisfy the required SINR or their attached femto stations reach theirmaximum allowed power.

A problem that may occur with FF-AP is that it does not take intoconsideration the effect of the power increase over the macro UEs SINR,which may lead to reducing the performance of the macro UEs. To overcomethis problem, certain embodiments add a macro constraint over the FF-AP,as described below.

D. Favoring Macro Users through Macro Focused Adaptive Power Adaptation(MF-AP)

In MF-AP, femto stations are each given a maximum power. If the femtostation is interfering with a macro UE, it decreases its power until themacro UEs reach the SINR needed. In case of any change in femto stationpower, re-association is done to all users in the network based on thenew power plan. Then, the process repeats until either all macro UEssatisfy the required SINR or their attached femto stations reach theirmaximum allowed power. But, MF-AP may lead the femto UEs to suffergreatly due to a high decrease in the femto station power. Thus,described below, certain embodiments avoid this problem by usingMF-AP-FC.

E. Favoring Macro Users through Macro SINR Constraint over the FF-AP(FF-AP-MC)

The FF-AP with macro constraint (FF-AP-MC) is similar to the AP schemebut it adds a variable into consideration, the macro UE SINR. FF-AP-MCprovides a compromise between both groups of users. Femto users are notserved as well as they are in normal AP-FF because their QoS is nolonger guaranteed to be satisfied. Macro UEs are not over burdened byhigh power from the femto station. If macro UEs surpass the thresholdlimit, the femto station is not allowed to further increase its power.

FIG. 13 is a flow chart of an example method 1300 using FF-AP-MCaccording to one embodiment. The method 1300 includes setting 1310 thefemto stations to a low power and querying 1312 whether the femto SINRis less than a target femto UE QoS. If no, the method 1300 ends 1314.If, however, the femto SINR is less than the target femto UE QoS, themethod 1300 reports 1316 to the femto station attached to the UE andqueries 1318 whether the femto station power is less than a maximumpower for the femto station. If no, the method 1300 ends 1320. If, onthe other hand, the femto station power is less than the maximum powerof the femto station, the method 1300 queries 1322 whether the macro UESINR is greater than a target macro UE QoS. If no, the method 1300 ends1324. If, however, the macro UE SINR is greater than the target macro UEQoS, the method 1300 increments 1326 the femto station power andreattaches all users based on the new power plan. Then, the method 1300repeats until all femto UEs satisfy the target femto SINR, theirattached femto stations reach their maximum allowed power, or all macroUEs satisfy the target macro SINR.

Thus, if any macro UE SINR is below the constraint value of Macro SINR,the femto station causing interference to the macro UE cannot increaseits power, and hence, no more interference occurs over the macro UE. Incertain embodiments, the constraint is not based over the macro-onlyscenario or to avoid a risk of disassociating the femto UE as the femtostation power is not allowed to increase to an acceptable level. In anexample embodiment, the constraint is 30% of the SINR CDF of macro UEsin the femto baseline. In certain embodiments, A-ICIC is added to macroperformance.

F. Favoring Femto Users through Femto SINR Constraint over the MF-AP(MF-AP-FC)

As macro constraint is applied to FF-AP, according to certainembodiments, femto constraint is applied to MF-AP. All femto stationsstart transmitting at their maximum power level, and decrement to reachthe macro SINR level. But, in case the SINR of the femto UEs attached tothe femto station go below a certain threshold, the femto station doesnot lower its power.

G. AP-Macro Constraint-A-ICIC (AP-MC-A-ICIC)

In certain embodiments, AP-MC-A-ICIC is used to improve over AP-MC. AsAP-MC takes macro UEs into consideration, A-ICIC may be added to ensurebetter performance of cell edge users. A-ICIC only affects usersconnected to femto stations interfering with a macro UE. After applyingAP-MC, the number of stations causing interference over macro UEs isless due to the power change. Thus, the decrease in capacity due toapplying A-ICIC is minimal. The power of the femto station in AP-MC islower than that of AP only because in AP-MC the femto UEs are notguaranteed to reach their QoS level, due to macro constraint. Thus, thepower of the femto stations can stay below satisfying the femto UEs.Applying A-ICIC means that any femto causing interference to a macro UEfrees part of its resources for use by macro UEs without femtointerference. This implies better performance for the macro UEs. Also,macro UEs in such embodiments are guarded against high interference byhaving a constraint over the femto power by using the macro UE QoSparameter to limit the ability of the femto station to increase power.Thus, the interference level may be controlled. In certain embodiments,AP-MC-A-ICIC provides a useful compromise between cell edge and capacitybecause it allows for a high capacity increase with a very low decreasein cell edge, as compared to a femto baseline.

VII. EXAMPLE PERFORMANCE ANALYSIS

Table 5 shows example results of running different simulations for 20runs. In this example, the Femto cells and UE deployment differ from onerun to the other to cover different states of randomization. Each runsimulates 100 frames.

TABLE 5 Simulation Results CELL CAPACITY CELL-EDGE % OF FSs SCENARIO(b/s/Hz) (b/s/Hz) AFFECTED FF-AP 12.568 0.037 N/A MF-AP 10.433 0.041 N/AFF-AP-MC 12.371 0.041 N/A MF-AP-FC 10.601 0.037 N/A MF-AP-ICIC 6.5460.043 100 MF-AP-A-ICIC 9.583 0.027 24.4 FF-AP-MC-A-ICIC 11.19 0.047 23

In Table 5, the AP embodiments may be evaluated against variousscenarios shown in Table 4: macro-only, femto baseline, ICIC, and APbasic algorithms. These algorithms are evaluated in terms of total areaSE and the cell-edge SE. In this example, the total area SE is the SEachieved over the sector area, which includes one macro station and sixfemto stations. In the macro-only scenario, none of the femto stationstransmits data, while the femto baseline case represents the scenario inwhich all the femto stations are transmitting with no interferencecoordination. Also, in this example, the AP technique had a maximumfemto station power of 20 dBm, a minimum femto station power of −10 dBm,a femto SINR target of 25% of CDF of femto UEs SINR before doing APwhich was 10, and an increment of change of 2 dBm. All A-ICIC and ICICare based on 50% shut off of resources.

Table 5 shows that the MF-AP technique provides for a minimal macro SINRlevel, which leads to an improvement in the performance of the macro UEsthat are below the target SINR. Thus, the MF-AP algorithm decreases thegap between femto baseline and macro-only cell edge to 16% with an areaSE of 372.98%, as compared to the macro-only scenario.

The FF-AP technique gives a guarantee of a femto SINR level, which leadsto an improvement in the performance of the femto UEs that are below thetarget SINR. Consequently, the FF-AP algorithm achieves higher area SEof 469.78%, and a cell-edge SE increase of 22.33%, as compared to themacro-only scenario. The increase in cell edge is justified for thedecrease in power of the femto station, which leads to an increase inthe SINR of the macro UEs.

The MF-AP-ICIC leads to an increase of 43% in cell edge but with anincrease of only 197% in capacity. MF-AP-A-ICIC produces a higherincrease in capacity than AP-ICIC, as it provides a 334% increase overthe macro-only, but AP-A-ICIC does not maintain the increase in celledge as it gives a cell edge decrease of around 10%. The 10% decrease isaround 30% of the decrease in the A-ICIC without AP and such a decreasein cell edge may be considered an acceptable sacrifice in someembodiments for the increase in capacity.

It is shown in Table 5 for FF-AP-MC that femto throughput is lower thanthat of unanimous power because not all femto users may be able tosatisfy their SINR condition, as some of the femto users are restrictedby the macro constraint. But, because the macro constraint is low due tobeing based on femto baseline and not the macro-only scenario, the femtostations are able to provide a good increase in cell edge of 460%, whichis very close to the 463% increase provided by the AP. FF-AP-MC is alsoless complex than adding ICIC and depends on best resource utilization,as it allows all femto resources to be used by femto users that areoriginally allocated to them. Consequently, the resources are given tolow interference users.

Further, FF-AP-MC provides for very low femto power in comparison toconstant power. The mean power for FF-AP-MC is around −4 dBm to −2 dBm,while the power used in the femto baseline is 20 dBm in all cases. FIG.14 is a graph illustrating femto station power after applying AP andAP-MC according to certain embodiments. There is a decrease in femtostation power using AP. However, as shown in FIG. 14, the power decreaseis slightly more for AP-MC because the constraint leads to notincreasing power so as to satisfy the SINR value for femto users.

In the example shown in Table 5, MF-AP-FC improves MF-AP by increasingthe cell edge and throughput over those of the MF-AP. Because MF-AP doesnot take into consideration femto UEs, it may lead femto UEsdisattaching from the very low power femto station and instead attachingto the macro station without a guarantee of their SINR level becausethey would be considered by the network as femto UEs. Consequently, thefemto UEs may act as cell edge UEs with a decrease of around 15% celledge from the macro-only. However, in certain MF-AP-FC embodimentsdisclosed herein, the limit of the FC constraint guarantees that allfemto stations can serve their UEs and that there is no need todisassociate. Consequently, cell edge greatly increases above that ofMF-AP to reach around 23% increase from macro-only, instead of adecrease of 15% in MF-AP. Also, MF-AP-FC increases cell capacity byaround 380% compared to macro-only, which is 7% higher from the MF-APincrease.

In AP-MC-A-ICIC, A-ICIC is done after applying FF-AP-MC. In the exampleshown in Table 5, the performance of FF-AP-MC is the best in conservinggood cell edge from the power control techniques. Thus, A-ICIC may bechosen to avoid sacrificing unnecessary capacity to improve alreadyacceptable cell edge. In AP-MCA-ICIC, the macro constraint does notprohibit interference over macro resources, so macro users' improvementcan be achieved through applying ICIC. In applying ICIC, it is notedthat the percentage of femto stations affected decreases from 24.4% inAP-A-ICIC to 23% in AP-MC-A-ICIC. This decrease may occur because theSINR of the macro UEs is already adjusted not to be below a certainlevel. Consequently, the percentage of interfering femto stations isless. AP-MC-A-ICIC gives an increase in capacity with 407.340%, which islower than AP-MC because of applying ICIC to 23% of the femto stations.AP-MC-A-ICIC cell edge increase is around 55% compared to macro-only.Thus, in this example, AP-MC-A-ICIC comes second in providing cell edgeafter the 90% increase from the AP-ICIC technique. Moreover,AP-MC-A-ICIC gives a very satisfying increase in capacity of around 4times the capacity provided by the macro-only technique. In thisexample, none of the other considered techniques achieve such a highcell edge as the AP-MC-A-ICIC with such a high increase in capacity.

In summary, heterogeneous networks increase the capacity and performanceof mobile communications networks by adding low power nodes. One type oflow power nodes is femto cells. A major challenge facing heterogeneousnetworks is the interference between different power nodes and itsdramatic effect on the macro UEs. The AP-ICIC and the AP-C are twoembodiments disclosed herein to solve this problem. AP-ICIC, on onehand, shuts off some of the femto resource blocks or directs the femtotransmission away from the macro transmission to increase the macroindoor UEs' SE and hence increases the cell-edge SE. On the other hand,AP-ICIC adjusts the femto station's transmission power to achieve thedesired femto UE QoS and hence increases the area SE. The AP-ICIC canproduce increased area SE of 245% over homogeneous networks that onlyuse macro stations, and can produce a cell edge increase of 94% versus adecrease in cell edge of 60% produced when adding femto cells with nointerference mitigation technique.

FF-AP-MC and MF-AP-FC solve a problem of FF-AP and MF-AP, respectively,which is not taking the other UE group into consideration. Theembodiments add a constraint over the AP technique to avoid putting highinterference over the macro indoor UEs. FF-AP-MC may give an increase incapacity of about 460% with a cell edge increase of about 37% comparedto macro-only, with a much lower complexity than ICIC techniques andwith high power saving. Also MF-AP-FC improves over the MF-AP as itgives about a 380% increase in capacity and a 23% increase in cell edge.A better cell edge may be produced from MF-AP-FC when adding A-ICIC tohave AP-MC-A-ICIC. AP-MC-A-ICIC may give a cell edge increase of about55% with an increase in capacity of about 407%, which ranks second bestin cell edge and increases capacity by four times compared to macro-onlytechniques, beside saving power as most femto stations may be sending atmuch lower than their maximum power. But, AP-MC-A-ICIC may have a highcomplexity.

Some of the infrastructure that can be used with embodiments disclosedherein is already available, such as general-purpose computers, mobilephones, computer programming tools and techniques, digital storagemedia, and communications networks. A computing device may include aprocessor such as a microprocessor, microcontroller, logic circuitry, orthe like. The computing device may include a computer-readable storagedevice such as non-volatile memory, static RAM, dynamic RAM, ROM,CD-ROM, disk, tape, magnetic, optical, flash memory, or othercomputer-readable storage medium.

Various aspects of certain embodiments may be implemented usinghardware, software, firmware, or a combination thereof. A component ormodule may refer to, be part of, or include an application specificintegrated circuit (ASIC), an electronic circuit, a processor (shared,dedicated, or group), and/or memory (shared, dedicated or group) thatexecute one or more software or firmware programs, a combinational logiccircuit, and/or other suitable components that provide the describedfunctionality. As used herein, a software module or component mayinclude any type of computer instruction or computer executable codelocated within or on a non-transitory computer-readable storage medium.A software module or component may, for instance, comprise one or morephysical or logical blocks of computer instructions, which may beorganized as a routine, program, object, component, data structure,etc., which performs one or more tasks or implements particular abstractdata types.

In certain embodiments, a particular software module or component maycomprise disparate instructions stored in different locations of acomputer-readable storage medium, which together implement the describedfunctionality of the module or component. Indeed, a module or componentmay comprise a single instruction or many instructions, and may bedistributed over several different code segments, among differentprograms, and across several computer-readable storage media. Someembodiments may be practiced in a distributed computing environmentwhere tasks are performed by a remote processing device linked through acommunications network.

Although the foregoing has been described in some detail for purposes ofclarity, it will be apparent that certain changes and modifications maybe made without departing from the principles thereof. It should benoted that there are many alternative ways of implementing both theprocesses and apparatuses described herein. Accordingly, the presentembodiments are to be considered illustrative and not restrictive, andthe invention is not to be limited to the details given herein, but maybe modified within the scope and equivalents of the appended claims.

Those having skill in the art will appreciate that many changes may bemade to the details of the above-described embodiments without departingfrom the underlying principles of the invention. The scope of thepresent invention should, therefore, be determined only by the followingclaims.

The invention claimed is:
 1. A method for interference mitigation in aheterogeneous network including one or more femto cells within a macrocell coverage area, the method comprising: transmitting, at a femtostation, wireless communication signals using a plurality of femtostation resources to communicate with at least one femto user equipment(UE) within a femto coverage area of the femto station, wherein theplurality of femto station resources are divisions of a shared mediumavailable to the femto station; detecting, at the femto station, that amacro UE is operating within the femto coverage area, wherein the macroUE is coupled to a macro station; in response to detecting the macro UE,shutting off a first portion of the femto station resources andtransmitting the wireless communication signals using a second portionof the femto station resources, wherein the first portion of the femtostation resources are a source of interference to the macro UE, whereindetecting the macro UE operating within the coverage area of the femtostation comprises: measuring a first power of a first signal received atthe femto station from the macro UE: receiving, at the femto station, amessage from a macro station indicating a second power of a secondsignal received at the macro station from the macro UE; and determiningthat the first signal is greater than the second signal, thedetermination indicating that the macro UE is detected within thecoverage area of the femto station.
 2. The method of claim 1, whereindetecting the macro UE operating within the coverage area of the femtostation comprises: receiving, at the femto station, a message from themacro UE indicating that power of a first signal received by the macroUE from a macro station is lower than power of a second signal receivedfrom the femto station.
 3. The method of claim 1, wherein detecting themacro UE operating within the coverage area of the femto stationcomprises: receiving a location message, at the femto station,indicating a geographic location of the macro UE; and determining thatthe geographic location of the macro UE is within the coverage area ofthe femto station.
 4. The method of claim 3, wherein the locationmessage is received from the macro UE.
 5. The method of claim 3, whereinthe location message is received from a macro station.
 6. The method ofclaim 1, further comprising: selectively adjusting a percentage of theplurality of femto station resources included in the first portion thatare shut off as a function of desired capacity available to the at leastone femto UE versus a desired improvement in a quality of serviceprovided to the macro UE.
 7. The method of claim 6, wherein increasingthe percentage of the plurality of femto station resources included inthe first portion decreases the capacity available to the at least onefemto UE.
 8. The method of claim 1, wherein one or more of the pluralityof femto station resources included in the first portion comprise atleast one of a time resource block and a frequency resource block. 9.The method of claim 1, further comprising: determining that the macro UEis no longer operating within the femto coverage area; and in responseto the determination, turning on the first portion of the femto stationresources to transmit the wireless communication signals using both thefirst portion and the second portion of the femto station resources. 10.The method of claim 1, wherein the at least one femto UE is associatedwith a closed subscription group (CSG) that grants access to communicatethrough the femto station, and wherein the macro UE is not associatedwith the CSG and is not granted access to communicate through the femtostation.
 11. The method of claim 1, further comprising: setting a firsttransmission power of the femto station; at the first transmissionpower, measuring a quality of service (QoS) for the at least one femtoUE within the femto coverage area; comparing the measured QoS for the atleast one femto UE with a first target QoS; and incrementally increasingthe power of the femto station from the first transmission power to asecond transmission power at which the first target QoS is met for eachof the at least one femto UE within the femto coverage area.
 12. Themethod of claim 11, further comprising, before each incremental increasein the power of the femto station: measuring a QoS for the macro UEdetected within the femto coverage area; comparing the measured QoS forthe macro UE with a second target QoS; and in response to determiningthat the second target QoS is satisfied for the macro UE, allowing theincremental increase in the power of the femto station.
 13. The methodof claim 1, further comprising: setting a first transmission power ofthe femto station; at the first transmission power, measuring a qualityof service (QoS) for the macro UE detected within the femto coveragearea; comparing the measured QoS with a first target QoS; anddecrementing the power of the femto station from the first transmissionpower to a second transmission power at which the first target QoS ismet for the macro UE within the femto coverage area.
 14. The method ofclaim 13, further comprising, before each decrement in the power of thefemto station: measuring a QoS for the at least one femto UE within thefemto coverage area; comparing the measured QoS for the at least onefemto UE with a second target QoS; and in response to determining thatthe second target QoS is satisfied for the at least one femto UE withinthe femto coverage area, allowing the decrement in the power of thefemto station.
 15. A non-transitory machine readable storage mediumhaving stored thereon instructions, which when executed by a processor,cause the processor to perform a method comprising: transmitting, from atransceiver, wireless communication signals using a plurality ofresources to communicate with a first user equipment (UE) within acoverage area of the transceiver, wherein the plurality of femto stationresources are divisions of a shared medium available to the femtostation; detecting, at the transceiver, that a second UE is operatingwithin the coverage area wherein the second UE is coupled to a macrostation; in response to detecting the second UE, shutting off a portionof the resources to reduce interference to the second UE, whereindetecting the macro UE operating within the coverage area of the femtostation comprises: measuring a first power of a first signal received atthe femto station from the macro UE; receiving, at the femto station, amessage from a macro station indicating a second power of a secondsignal received at the macro station from the macro UE; and determiningthat the first signal is greater than the second signal, thedetermination indicating that the macro UE is detected within thecoverage area of the femto station.
 16. The machine readable storagemedium of claim 15, the method further comprising: setting a firsttransmission power of the transceiver; at the first transmission power,measuring a quality of service (QoS) for the first UE within thecoverage area; comparing the measured QoS for the first UE with a firsttarget QoS; and incrementally increasing the power of the transceiverfrom the first transmission power to a second transmission power atwhich the first target QoS is met for the first UE within the coveragearea.
 17. The machine readable storage medium of claim 16, the methodfurther comprising, before each incremental increase in the power of thetransceiver: measuring a QoS for the second UE detected within thecoverage area; comparing the measured QoS for the second UE with asecond target QoS; and in response to determining that the second targetQoS is satisfied for the second UE, allowing the incremental increase inthe power of the transceiver.
 18. The machine readable storage medium ofclaim 15, the method further comprising: setting a first transmissionpower of the transceiver; at the first transmission power, measuring aquality of service (QoS) for the second UE detected within the coveragearea; comparing the measured QoS with a first target QoS; anddecrementing the power of the transceiver from the first transmissionpower to a second transmission power at which the first target QoS ismet for the second UE.
 19. The machine readable storage medium of claim18, the method further comprising, before each decrement in the power ofthe transceiver: measuring a QoS for the first UE within the coveragearea; comparing the measured QoS for the first UE with a second targetQoS; and in response to determining that the second target QoS issatisfied for the first UE within the coverage area, allowing thedecrement in the power of the transceiver.
 20. A method for interferencemitigation in a heterogeneous network including one or more femto cellswithin a macro cell coverage area, the method comprising: transmitting,at a femto station, wireless communication signals using a plurality offemto station resources to communicate with at least one femto userequipment (UE) within a femto coverage area of the femto station;detecting, at the femto station, that a macro UE is operating within thefemto coverage area, wherein the macro UE is coupled to a macro station;setting a first transmission power of the femto station; at the firsttransmission power, measuring a quality of service (QoS) for the atleast one femto UE within the femto coverage area; comparing themeasured QoS for the at least one femto UE with a first target QoS;incrementally increasing the power of the femto station from the firsttransmission power to a second transmission power at which the firsttarget QoS is met for each of the at least one femto UE within the femtocoverage area; measuring a QoS for the macro UE detected within thefemto coverage area; comparing the measured QoS for the macro UE with asecond target QoS; and in response to determining that the second targetQoS is satisfied for the macro UE, allowing the incremental increase inthe power of the femto station, and further comprising in response todetecting the macro UE, shutting off a first portion of the femtostation resources and transmitting the wireless communication signalsusing a second portion of the femto station resources, wherein the firstportion of the femto station resources are a source of interference tothe macro UE and wherein the plurality of femto station resources aredivisions of a shared medium available to the femto station.
 21. Themethod of claim 20, wherein detecting the macro UE operating within thecoverage area of the femto station comprises: receiving, at the femtostation, a message from the macro UE indicating that power of a firstsignal received by the macro UE from a macro station is lower than powerof a second signal received from the femto station.
 22. The method ofclaim 20, wherein detecting the macro UE operating within the coveragearea of the femto station comprises: measuring a first power of a firstsignal received at the femto station from the macro UE; receiving, atthe femto station, a message from a macro station indicating a secondpower of a second signal received at the macro station from the macroUE; and determining that the first signal is greater than the secondsignal, the determination indicating that the macro UE is detectedwithin the coverage area of the femto station.
 23. The method of claim20, wherein detecting the macro UE operating within the coverage area ofthe femto station comprises: receiving a location message, at the femtostation, indicating a geographic location of the macro UE; anddetermining that the geographic location of the macro UE is within thecoverage area of the femto station.
 24. The method of claim 23, whereinthe location message is received from the macro UE.
 25. The method ofclaim 23, wherein the location message is received from a macro station.26. The method of claim 20, wherein the at least one femto UE isassociated with a closed subscription group (CSG) that grants access tocommunicate through the femto station, and wherein the macro UE is notassociated with the CSG and is not granted access to communicate throughthe femto station.
 27. A method for interference mitigation in aheterogeneous network including one or more femto cells within a macrocell coverage area, the method comprising: transmitting, at a femtostation, wireless communication signals using a plurality of femtostation resources to communicate with at least one femto user equipment(UE) within a femto coverage area of the femto station; detecting, atthe femto station, that a macro UE is operating within the femtocoverage area, wherein the macro UE is coupled to a macro station;setting a first transmission power of the femto station; at the firsttransmission power, measuring a quality of service (QoS) for the macroUE detected within the femto coverage area; comparing the measured QoSwith a first target QoS; decrementing the power of the femto stationfrom the first transmission power to a second transmission power atwhich the first target QoS is met for the macro UE within the femtocoverage area; measuring a QoS for the at least one femto UE within thefemto coverage area; comparing the measured QoS for the at least onefemto UE with a second target QoS; and in response to determining thatthe second target QoS is satisfied for the at least one femto UE withinthe femto coverage area, allowing the decrement in the power of thefemto station, and further comprising in response to detecting the macroUE, shutting off a first portion of the femto station resources andtransmitting the wireless communication signals using a second portionof the femto station resources, wherein the first portion of the femtostation resources are a source of interference to the macro UE andwherein the plurality of femto station resources are divisions of ashared medium available to the femto station.
 28. The method of claim27, wherein detecting the macro UE operating within the coverage area ofthe femto station comprises: receiving, at the femto station, a messagefrom the macro UE indicating that power of a first signal received bythe macro UE from a macro station is lower than power of a second signalreceived from the femto station.
 29. The method of claim 27, whereindetecting the macro UE operating within the coverage area of the femtostation comprises: measuring a first power of a first signal received atthe femto station from the macro UE; receiving, at the femto station, amessage from a macro station indicating a second power of a secondsignal received at the macro station from the macro UE; and determiningthat the first signal is greater than the second signal, thedetermination indicating that the macro UE is detected within thecoverage area of the femto station.
 30. The method of claim 27, whereindetecting the macro UE operating within the coverage area of the femtostation comprises: receiving a location message, at the femto station,indicating a geographic location of the macro UE; and determining thatthe geographic location of the macro UE is within the coverage area ofthe femto station.
 31. The method of claim 30, wherein the locationmessage is received from the macro UE.
 32. The method of claim 30,wherein the location message is received from a macro station.
 33. Themethod of claim 27, wherein the at least one femto UE is associated witha closed subscription group (CSG) that grants access to communicatethrough the femto station, and wherein the macro UE is not associatedwith the CSG and is not granted access to communicate through the femtostation.